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Business Statistics: Is Forecasting Market Prices Truly Achievable?

Depending on your school of thought, forecasting market prices can be either a waste of time or the key to financial success. Either way, knowing about each camp is useful as you learn about business statistics.

Forecasting is especially important in the field of finance. Investors try to decide which assets to buy or sell based on their own expectations of future market conditions — including stock prices, interest rates, exchange rates, and commodity prices. A great deal of time and effort is put into forecasting activities, because correctly anticipating the future values of these variables can help investors earn unusually high returns. But are all these efforts wasted?

Casting doubt on forecasting: The Efficient Markets Hypothesis (EMH)

One branch of economic theory holds that forecasting future market prices is unlikely to be successful. This theory is known as the Efficient Markets Hypothesis (EMH); it was proposed by University of Chicago economist Eugene Fama in 1965. According to the EMH, financial markets are highly efficient, so all available information is instantly reflected in stock prices. Therefore, attempting to forecast stock prices from their past performance is a complete waste of time and money.

One of the major proponents of this view is Burton Malkiel, whose book A Random Walk Down Wall Street (W.W. Norton & Company) has sold more than 1 million copies since it was first published in 1973. The premise of this book is that stock prices follow a "random walk." In this process, a variable randomly fluctuates up and down over time, without following any particular pattern. As a result, past stock prices can't be used to profitably forecast future stock prices.

Learning from the past with technical analysis and statistical arbitrage

Many people disagree with the premise that markets are so efficient that forecasting prices from past performance is impossible. One such group includes traders who use a strategy known as technical analysis. With this approach, people analyze past prices of an asset to find patterns that can be used to predict future prices. The widespread use of technical analysis on Wall Street indicates that many market participants aren't convinced of the efficiency of financial markets.

Another group is hedge funds who specialize in a strategy known as statistical arbitrage. This approach involves the use of computers to analyze massive quantities of historical data to find small discrepancies in market prices (that is, market inefficiencies) and profit from them. Some of these statistical arbitrage funds have been quite successful, indicating that the markets may be highly efficient but not perfectly efficient. In this case, investors may still use forecasting to improve the returns to their portfolios.

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